The contempt laden Op-Ed is here. Below is the first paragraph:
In his inaugural address, Barack Obama promised to restore science to its”rightful place.”This has partly occurred, as evidenced by this month’s release of 13 new human embryonic stem-cell lines. The recent brouhaha over the guidelines put forth by the government task force on breast-cancer screening, however, illustrates how tricky it can be to deliver on this promise. One big reason is that people may not like or even understand what scientists say, especially when what they say is complex, counterintuitive or ambiguous.
So right out of the box author John Allen Paulos rhetorically links the G.W. Bush era right wing “Christianity” driven opposition to stem cell research with concerns about the new mammogram guidelines. But that noxious opener is completely unfair. Women did not start scheduling mammograms for dubious religious reasons. We did it because SCIENTISTS CONVINCED US IT WOULD BE BENEFICIAL – scientists at places like the Centers For Disease Control. So did organizations like the American Cancer Society, which last time I checked was not “faith based.”
In the next sentence Paulos moves from despicable analogy to outright lies. He writes:
As we now know, the panel of scientists advised that routine screening for asymptomatic women in their 40s was not warranted and that mammograms for women 50 or over should be given biennially rather than annually.
How often are women getting mammograms? According to this American Cancer Society report: “Mammography usage has not increased since 2000. In 2005, 51.2% of women aged 40 and older reported getting a mammogram in the past year. Women who lack health insurance have the lowest use of mammograms (24.1%).” Have breast cancer deaths decreased since breast cancer screening has increased? Yes they have. Did Paulos actually read the report? Because I did, and as I blogged previously, here is what it said:
There is convincing evidence that screening with film mammography reduces breast cancer mortality, with a greater absolute reduction for women aged 50 to 74 years than for women aged 40 to 49 years. The strongest evidence for the greatest benefit is among women aged 60 to 69 years. …
How will reduced screening change these numbers? We don’t know. Here is another excerpt from the Report:
A series of randomized clinical trials that would compare the results of stopping breast cancer screening at different ages (by first comparing stopping screening at age 75 years with continued screening, and then further comparing stopping screening at earlier ages, depending on the results of the first study) would be ethical and informative.
Extended follow-up of this type of study might also provide useful information about overdiagnosis in this age group. In general, more studies of overdiagnosis, including comparisons of lifetime breast cancer incidence among similar screened and unscreened women, would be helpful. Studies on overdiagnosis might also include long-term follow-up of women with probable missed cases of DCIS on the basis of microcalcifications that were missed in an earlier mammogram. Such studies could provide the percentage of these women who develop invasive breast cancer over the next 10 or more years.
Randomized clinical trials of film versus digital mammography among women with dense breast tissue, with sufficient follow-up to detect stage shifts (reductions of late-stage cancer) or decreases in clinical interval cases, would also be ethical and helpful.
Better understanding of certain facets of tumor biology is needed, particularly how age, race, breast density, and other factors may predispose certain women toward tumors with faster growth rates and greater lethality. This would improve the ability to determine at diagnosis which patients can be treated minimally.
In short, the Report is pretty equivocal about whether reducing breast cancer screening will have net benefits beyond cost savings, reducing”psychological harms, unnecessary imaging tests and biopsies in women without cancer, and inconvenience due to false-positive screening results,”and overdiagnosis. How much overdiagnosis? We don’t know. The Report admits:”Methods for estimating overdiagnosis at a population level are not well established, and thus the proportion of all detected DCIS lesions that constitute overdiagnosis is uncertain.”
But let’s get back to Paulos:
Fortunately, both the panel’s concerns and the public’s reaction to its recommendations may be better understood by delving into the murky area between mathematics and psychology.
Now we get to learn in more detail how stupid he thinks women are, as a matter of psychology and poor math skills:
Much of our discomfort with the panel’s findings stems from a basic intuition: since earlier and more frequent screening increases the likelihood of detecting a possibly fatal cancer, it is always desirable. But is this really so? Consider the technique mathematicians call a reductio ad absurdum, taking a statement to an extreme in order to refute it. Applying it to the contention that more screening is always better leads us to note that if screening catches the breast cancers of some asymptomatic women in their 40s, then it would also catch those of some asymptomatic women in their 30s. But why stop there? Why not monthly mammograms beginning at age 15?
Yes, and why stop with monthly mammograms at age 15? You broads are so dumb, when the doctor tells you to take one pill per day for a month, you probably swallow all thirty at once, thinking this will cure you faster. Just because medical professionals advised you for years that a yearly mammogram would help protect your health, doesn’t mean you should have believed them. But now that a brainy mathematician like Paulos says you shouldn’t have them as frequently, you should absolutely listen, because clearly he’s right and every shred of available evidence supports his position. Or does it? More Paulos:
…Alas, it’s not easy to weigh the dangers of breast cancer against the cumulative effects of radiation from dozens of mammograms, the invasiveness of biopsies (some of them minor operations) and the aggressive and debilitating treatment of slow-growing tumors that would never prove fatal.
The exact weight the panel gave to these considerations is unclear …
Alas? Not easy to weigh? Unclear? Huh, suddenly it appears maybe the new recommendations aren’t so definitive after all. So on to abstract mathematical modeling with made-up numbers:
… A little vignette with made-up numbers may shed some light. Assume there is a screening test for a certain cancer that is 95 percent accurate; that is, if someone has the cancer, the test will be positive 95 percent of the time. Let’s also assume that if someone doesn’t have the cancer, the test will be positive just 1 percent of the time. Assume further that 0.5 percent : one out of 200 people : actually have this type of cancer. Now imagine that you’ve taken the test and that your doctor somberly intones that you’ve tested positive. Does this mean you’re likely to have the cancer? Surprisingly, the answer is no.
To see why, let’s suppose 100,000 screenings for this cancer are conducted. Of these, how many are positive? On average, 500 of these 100,000 people (0.5 percent of 100,000) will have cancer, and so, since 95 percent of these 500 people will test positive, we will have, on average, 475 positive tests (.95 x 500). Of the 99,500 people without cancer, 1 percent will test positive for a total of 995 false-positive tests (.01 x 99,500 = 995). Thus of the total of 1,470 positive tests (995 + 475 = 1,470), most of them (995) will be false positives, and so the probability of having this cancer given that you tested positive for it is only 475/1,470, or about 32 percent! This is to be contrasted with the probability that you will test positive given that you have the cancer, which by assumption is 95 percent.
That clear things up for you? No? It’s because you are stupid, obviously:
… Most people don’t naturally think probabilistically, nor do they respond appropriately to very large or very small numbers. For many, the only probability values they know are”50-50″and”one in a million.”Whatever the probabilities associated with a medical test, the fact remains that there will commonly be a high percentage of false positives when screening for rare conditions. Moreover, these false positives will receive further treatments, a good percentage of which will have harmful consequences. This is especially likely with repeated testing over decades.
Note Paulos doesn’t actually know the probabilities associated with mammograms. He just generalizes that “there will commonly be a high percentage of false positives” when screening for “rare conditions.” Is breast cancer truly a rare condition? Scientists at the American Cancer Society do not think so. But let’s get back to how stupid women are, that’s a lot more fun than data, apparently:
… Cognitive biases also make it difficult to see the competing desiderata the panel was charged with balancing. One such bias is the availability heuristic, the tendency to estimate the frequency of a phenomenon by how easily it comes to mind. People can much more readily picture a friend dying of cancer than they can call up images of anonymous people suffering from the consequences of testing. Another bias is the anchoring effect, the tendency to be overly influenced by any initially proposed number. People quickly become anchored to such a number, whether it makes sense or not (“we use only 10 percent of our brains”), and they’re reluctant to abandon it. If accustomed to an annual mammography, they’re likely for that reason alone to resist biennial (or even semiannual) ones. …
Women are so easily “anchored” to an “initially proposed number” that we would resist decreasing or increasing the number of mammograms we undergo no matter what our doctors recommend, that’s how dumb we are. Nice. And you just knew there would be a truly reprehensible conclusion, didn’t you? Paulos wraps up by saying:
Whatever the role of these biases, the bottom line is that the new recommendations are evidence-based. This doesn’t mean other right-thinking people would necessarily come to the same judgments. To oppose the recommendations, however, requires facts and argument, not invective.
Has the New York Times stopped requiring logic or coherence altogether? Let’s unpack this sentence by sentence:
Whatever the role of these biases, the bottom line is that the new recommendations are evidence-based.
Paulos doesn’t know what the role of these biases may be, but damn it felt good to accuse women of having them. And he says the new recommendations are “evidence based,” completely ignoring the fact that one key recommendation is that more research should be conducted, because so much important evidence is lacking.
This doesn’t mean other right-thinking people would necessarily come to the same judgments.
And in fact, they haven’t, as noted above. Which might be a good reason not to cast aspersions on women who are asking hard questions about the new guidelines.
To oppose the recommendations, however, requires facts and argument, not invective.
Maybe if people like Paulos were less condescending the invective would flow less freely. Women have good reasons to be cautious about “guideline changes” that give insurance companies cover to reduce the kind or quantity of health care that woman are able to receive. I’m keeping an open mind about the new guidelines, it would be nice if people like Paulos would do the same.
–Ann Bartow
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Ann – I truly enjoyed reading this article, and you’re absolutely correct, the condescension in the op-ed just drips with contempt for the intellectual capacity of women.
Since Paulos is so entombed in his math and probability equations, I wonder how he’d like to tackle a set of data from my own family? I have three male cousins, all brothers, and each of them have had wives who were diagnosed with breast cancer, had that diagnosis confirmed by – not one but three specialists – and have been successfully treated and survived that horrible malady. None of these women are blood related, none of them came from the same background, all have very different life habits, and yet all three came down with breast cancer.
Out of the millions of women in this world how “probable” is it that these three very random women would all have that terrible affliction? And what should we have done to have sought diagnosis? Which of my cousin-in-laws would Paulos have me tell “Sorry, the math just doesn’t add up for you”, while he sat there giddily clicking away at his calculator while one, two or all three of these women died?
I have three daughters, and three grand-daughters. Which of them should I look in the face and advise “Oh, you don’t need to worry about that, it’s just so statistically improbable that you’ll never come down with breast cancer. So relax and don’t worry about it.” And what should I tell them when it does, “Too bad, you were one of the few statistics in the cancer column.” Boy, that’ll make them feel better.
Sort of like “Don’t bother yourself with facts, little lady, they’ll only confuse you.” How much more condescending does it get? And what is for me the most disgusting feature of this screed on his part is that it won’t affect him, just women. How’s that for hatred?
On behalf of all the women in my life, Paulos, you go straight to Hell and stay there.
This report was so scientifically done that they didn’t even bother including a single oncologist or radiologist on the board that made the recommendations.
When you try to decide a policy issue like this on a scientific basis, you go with what the most knowledgeable people think. From the perspective of the efficacies of screening, the members of this board amounted to rank amateurs.
On that basis alone, this report needs to be rejected and a new study performed. Unfortunately, the latest news is 20 states have already adopted these recommendations.
The op-ed is rather disturbing but I think you missed one glaring falsehood “Much of our discomfort with the panel’s findings stems from a basic intuition: since earlier and more frequent screening increases the likelihood of detecting a possibly fatal cancer, it is always desirable.”
I believe that the major cause of the firestorm of controversy came from the timing of the report right in the middle of health care reform season. With the politicians filled with talk about “bending the cost curve” and accusations that care would be shorted for political and budgetary reasons, people were very much primed to be suspicious of any recommendation that reduced screenings were actually beneficial. The fact that the panel had no oncologists on it was an extra strike against it.
The reaction demonstrated public’s trust that the experts won’t lie in order to save a few bucks was exposed as being very low. And why shouldn’t it? The experts have lied before. Rogue science is at least as old as Piltdown man.
“We did it because SCIENTISTS CONVINCED US IT WOULD BE BENEFICIAL…”
This is a great point and in my opinion it’s right to be skeptical of the new recommendations and not make any rapid changes. Fortunately, the last I read was that insurance companies had no plans to change coverage.
Paulos is describing once again the conditional probability fallacy; it’s kind of his thing. But I think it’s irresponsible of him to use made up numbers. The incidence rate of breast cancer and the mammogram false positive rate are presumably well known, why not use the real numbers and give women an actual estimate of the probability that a positive mammogram means cancer?
However, I don’t think it’s fair to call him condescending–or at least not specifically to women. His basic point is that when a condition is sufficiently rare, a positive result on even a very accurate test is not as conclusive as any non-statistician, male or female, would expect. He could–and would, I think–write the same thing about prostate cancer screening.
You could argue that media in general are condescending to their audience, because each story on this should have P(cancer|positve) calculated and mentioned prominently. Paulos was evidently more interested in demonstrating how innumerate we are than in providing a useful service to the reader, but an editor could have asked for real numbers.
One of the fascinating aspects of this brouhaha over the recommendations to reduce mammograms (and I agree with your criticisms of the NY Times article entirely) is how different it’s been treated from similar studies released, and reported in the NY Times, last March, regarding analogous screening for the male cancer: Prostate Test Found to Save Few Lives.
I really don’t recall any editorials condemning men for blindly ignoring the latest science. There were, in fact, nuanced stories discussing whether in fact the benefits of screening outweighed the risks.
That should be the case here, of course. Every person should be allowed to decide for themselves when to start receiving such preventative screenings. Certainly the insurance company or government agency should place SOME limit on them; the rest of us shouldn’t subsidize a hypochondriac who wants monthly tests, for instance… but annually or biennially? Let the patient make that choice.
What’s next? Will they declare that if you don’t receive the recommended screenings, they won’t pay for treatment down the road?
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Hello,
You can rail against the journalists for their attempt to explain science, but in the end the science is still very messy.
Here are some reasonable facts which I think aren’t too controversial now:
1) X-Rays cause cancer in some small percent of cases.
2) Horse based Estrogen causes breast cancer. Now that it is isn’t used much any more, the cancer rate should be falling – without any help from screening.
3) Mammograms have found a lot of cancers which fell somewhere in between benign and malignant. They didn’t know what to do with these cancers, and many were treated as regular cancer. This caused lots of pain for woman, and at the same time an increased “survival rate”. Since a cancer which was treated is considered a success, but a cancer never found is not.
Add all this up, and you can most any conclusion you like (depending on your disposition). Granted woman tend to want “control” which may be comforting, even if it leads to bad results.
All this leads to my main point. Science tends to have a “crying wolf” problem. It comes out with some course of action, which often times is wrong, sometimes tragically wrong. Scientists then comes out later with an opposite course of action, which people then dismiss because the first course is now wrong – which destroys the credibility of the scientists.
When I was a kid, when we ate dinner, we ate are bread with margarine. This was because butter had saturated fat which caused heart disease. This went on for 20 or 30 years. Then one day, saturated fat no longer caused heart disease, and trans-fats caused heart disease. The advice to eat margarine was not only ineffective, it actually caused heart disease (tragically wrong)! Now people won’t believe that trans-fats cause heart disease, because the heart (vascular really) scientists who figured it out were the ones who told us not to eat the butter.
I don’t blame the scientists, its a hit and miss affair. But from my perspective, its an argument for freedom of choice in the end. The scientists will send out the data and recommendations, and we will have to choose individually. The dynamic of having the scientists lead us is too damaging when the story (inevitably) changes. I think that’s also an argument against socialized medicine, but your views may differ.
James
JamesB – I don’t blame scientists. The actual Report seems thoughtful and reasonable to me. It asks important questions and it doesn’t purport to be definitive. What troubles me is that that it may be used by insurance companies to limit or deny coverage for mammograms and other types of breast cancer screening, which would have a horrible impact on women who are at very high risk (because they took HRT, or because of their genetics, or a host of other reasons). The test for whether or not a woman had the so called “breast cancer gene” costs thousands of dollars and is not currently covered by many insurance plans. Now women at high risk for breast cancer could lose coverage for yearly screening as well, which their lives might depend upon.
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Ann, your comment above raises a very important issue, and everyone should distinguish (helpful) screening for women with identified risks (family history of breast cancer, use of HRT, or as you point out, a host of other reasons) and population-based screening, under which asymptomatic women who have no reason to have breast cancer are pushed (and yes, they are pushed) into screening.
But Paulos does have a point. We are conditioned to be scared of breast cancer. There are other deadly cancers for which we aren’t routinely screened. And while we all know women who have suffered terribly from breast cancer, we don’t know those women who were overtreated. Why? Because most of those women were told that they had cancer when they really had a stage zero condition with a small chance (maybe 20%) of turning into an invasive cancer.
You asked me in an earlier comment if I’m a physician. I’m not. I’m a DCIS victim. Note that I didn’t say “breast cancer survivor.” If you want to see women treated condescendingly, stop by a breast center. The only way that I found out that my condition had a very small chance of turning into invasive cancer was by doing my own research. Everyone at the breast center treated me like an uneducated housewife who was terrified of her awful cancer. Yes, I had the surgery, and in a “made for TV” moment, I learned about the new guidelines the morning after my follow up appointment. First, I smiled for all of those women who won’t be subjected to overtreatment for a condition that is unlikely to harm them. Then I cried.
Jay, I’m sorry you had a negative experience. But I do not think you have any evidence to support your assertion that “Because most of those [over treated] women were told that they had cancer when they really had a stage zero condition with a small chance (maybe 20%) of turning into an invasive cancer.” The Report says, as I quote above, “Methods for estimating overdiagnosis at a population level are not well established, and thus the proportion of all detected DCIS lesions that constitute overdiagnosis is uncertain.”How many women are over treated is unknown, and hopefully something that will be researched further. As I said, I think it is good to ask questions and demand better answers. That is not what Paulos is doing in his Op-Ed, however.
That recommendation was received with some sense of irony in my house as it came out exactly one day after my 39 year old wife was diagnosed with cancer from a routine mammogram. The mastectomy was yesterday.
Like Jay, we initially thought it was DCIS and went with a lumpectomy to remove it. But unlike in Jay’s case, there was an invasive tumor in there as well and a second surgery was necessary. If she waited until 50, she’d likely be one of those unfortunate statistics we’re apparently better off with than without.
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